Probabilistic methods of risk predictions and their pragmatic applications in life cycle of complex systems

• Autorzy: Kostogryzov Andrey , Nistratov Andrey

Identyfikatory

DOI

10.26408/srsp-2020-11

• Konferencja: 14th Summer Safety & Reliability Seminars - SSARS 2020, 26-30 September 2020, Ciechocinek, Poland
• Języki publikacji: EN

Abstrakty

EN

The probabilistic methods of risk predictions, focused on the prognostic modeling of complex systems, and their pragmatic applications are proposed. They are based on an implementation of the proposed interconnected ideas about system analysis in life cycle. The approach includes description of the probabilistic models, optimization methods for rationale actions and incremental algorithms for solving the problems of supporting decisionmaking and rationale preventive actions in uncertainty conditions. A suitability of the proposed models and methods is demonstrated by examples which cover wide reliability and safety applications for some intellectual systems, enterprises of coal company, a floating oil and gas platform, a set of manufacturing processes of gas preparation equipment, the systems of oil&gas transportation and distribution. The approach means practically proactive commitment to excellence in uncertainty conditions.

Słowa kluczowe

EN

analysis; model; operation; prediction; probability; rationale; risk; system; system engineering

• Wydawca: Gdynia Maritime University ; Polskie Towarzystwo Bezpieczeństwa i Niezawodności
• Czasopismo: Safety and Reliability of Systems and Processes
• Rocznik: 2020
• Tom: Summer Safety and Reliability Seminar 2020
• Strony: 153--174
• Opis fizyczny: Bibliogr. 39 poz., rys., tab.

Twórcy

autor

Kostogryzov Andrey

• Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Moscow, Russia

autor

Nistratov Andrey

• Scientific and EngineeringCentre for Energy Safety, Moscow, Russia

Bibliografia

• [1] Akimov, V., Kostogryzov, A., Mahutov, N. at al. 2015. Security of Russia. Legal, Social & Economic and Scientific&Engineering Aspects. The Scientific Foundations of Technogenic Safety. Under the editorship of Mahutov N.A. Znanie, Moscow.
• [2] Artemyev, V., Kostogryzov, A., Rudenko, Ju., Kurpatov, O., Nistratov, G. & Nistratov, A. 2017. Probabilistic methods of estimating the mean residual time before the next parameters abnormalities for monitored critical systems. Proceedings of the 2nd International Conference on System Reliability and Safety (ICSRS), Milano, Italy, 368-373.
• [3] Artemyev, V., Rudenko, Ju. & Nistratov, G. 2018: Probabilistic methods and technologies of risks prediction and rationale of preventive measures by using “smart systems”. Applications to coal branch for increasing industrial safety of enterprises. Probabilistic Modeling in System Engineering. A. Kostogryzov (Ed.), IntechOpen, 23-51.
• [4] Eid, M. & Rosato, V. 2016. Critical infrastructure disruption scenarios analyses via simulation. Managing the Complexity of Critical Infrastructures. A Modelling and Simulation Approach, SpringerOpen, 43-62.
• [5] Feller, W. 1971. An Introduction to Probability Theory and Its Applications. Vol. II, Willy.
• [6] Gnedenko, B. V. et al. 1973. Priority queueing systems, МSU, Moscow.
• [7] Grigoriev, L., Guseinov, Ch., Kershenbaum V. & Kostogryzov, A. 2014. The methodological approach, based on the risks analysis and optimization, to research variants for developing hydrocarbon deposits of Arctic regions. Journal of Polish Safety and Reliability Association. Summer Safety and Reliability Seminars 5(1-2), 71-78.
• [8] Kershenbaum, V., Grigoriev, L., Kanygin, P. & Nistratov, A. 2018. Probabilistic modeling in system engineering. Probabilistic Modeling Processes for Oil and Gas Systems. A. Kostogryzov (Ed.), IntechOpen, 55-79.
• [9] Kleinrock, L. 1976. Queueing Systems, V.2: Computer Applications, John Wiley & Sons, New York.
• [10] Kołowrocki, K. & Soszyńska-Budny, J. 2011. Reliability and Safety of Complex Technical Systems and Processes, Springer-Verlag London Limited.
• [11] Kostogryzov, A. & Korolev, V. 2020 Probability, combinatorics and control. Probabilistic Methods for Cognitive Solving Problems of Artificial Intelligence Systems Operating in Specific Conditions of Uncertainties. IntechOpen, 3-34.
• [12] Kostogryzov, A. & Nistratov, G. 2004. Standardization, Mathematical Modelling, Rational Management and Certification in the Field of System and Software Engineering (80 Standards, 100 Mathematical Models, 35 Software Tools, more than 50 Practical Examples). Armament. Policy. Conversion, Moscow.
• [13] Kostogryzov, A. I. & Nazarov, L. V. 1981. Batch processing of calls with relative priorities in queueing system, News of Academy of Sciences of the USSR “Engineering Cybernetics” 3, 194-198.
• [14] Kostogryzov, A. I. & Stepanov, P. V. 2008. Innovative Management of Quality and Risks in Systems Life Cycle (Modern Standards and Ideas of System Engineering, Mathematical Models, Methods, Techniques and Software Tools Complexes for System Analysis, Including Modelling through Internet, 100 Examples with an Explanation of Logic of the Reached Results, Useful Practical Recommendations). Moscow, Armament. Policy. Conversion, Moscow.
• [15] Kostogryzov, A. I. 1987. Conditions for efficient batch job processing of customers in prioritydriven computing systems where the queueing time is constrauned, Avtomatika i Telemehanika, 12, 158-164.
• [16] Kostogryzov, A. I. 1992. Study of the efficiency of combinations of different disciplines of the priority service of calls in the computer systems, Kibernetika i Sistemny Analiz, 1, 128-137.
• [17] Kostogryzov, A. I. 2000. Software tools complex for evaluation of iinformation systems operation quality (CEISOQ). Proceedings of the 34th Annual Event of the Government Electronics and Information Association (GEIA), Engineering and Technical Management Symposium, USA, Dallas, 63-70.
• [18] Kostogryzov, A. I., Bezkorovainy, M. M., Lvov, V. M., Nistratova, E. N., & Bezkorovainaya, I. V. 2000. Complex for Evaluation of Information Systems Operation Quality - “know-how” (CEISOQ), registered by Rospatent №2000610272.
• [19] Kostogryzov, A. I., Nistratov, G. A. & Nistratov, A. A. 2018. Remote Analytical Support of Informing about the Probabilistic and Time Measures of Operating System and its Elements for Risk-Based Approach, registered by Rospatent №2018617949.
• [20] Kostogryzov, A. I., Nistratov, G. A. & Nistratov, A. A. 2018. Remote Rationale of Requirements to Means and Conditions for Providing "Smart" Systems Operation Quality, registered by Rospatent №2018618572.
• [21] Kostogryzov, A. I., Nistratov, G. A., Nistratova, E. N. & Nistratov, A. A. 2004. Mathematical Modeling of System Life Cycle Processes - “Know-How”, registered by Rospatent №2004610858.
• [22] Kostogryzov, A. I., Nistratov, G. A., Nistratova, E. N., Nistratov, A. A. 2018. Complex for Evaluating Quality of Production Processes, registered by Rospatent №2010614145.
• [23] Kostogryzov, A. I., Petuhov, A. V. & Scherbina, A. M. 1994. Foundations of Evaluation, Providing and Increasing Output Information Quality for Automatized System. Moscow: Armament. Policy. Conversion.
• [24] Kostogryzov, A. I., Stepanov, P. V., Nistratov, G. A., Nistratov, A. A., Grigoriev, L. I. & Atakishchev, O. I. 2015. Innovative Management Based on Risks Prediction, Information Engineering and Education Science - Zheng (Ed.). Taylor & Francis Group, London, 159-166.
• [25] Kostogryzov, A., Atakishchev, O., Stepanov, P., Nistratov, A., Nistratov, G. & Grigoriev, L. 2017. Probabilistic modelling processes of mutual monitoring operators actions for transport systems. Proceedings of the 4th International Conference on Transportation Information and Safety (ICTIS), Canada, Banff, 865-871.
• [26] Kostogryzov, A., Grigoriev, L., Golovin, S., Nistratov, A., Nistratov, G. & Klimov, S. 2018. Probabilistic modeling of robotic and automated systems operating in cosmic space. Proceedings of the International Conference on Communication, Network and Artificial Intelligence (CNAI), Beijing, China. DEStech Publications, Inc., 298-303.
• [27] Kostogryzov, A., Grigoriev, L., Kanygin, P., Golovin, S., Nistratov, A. & Nistratov, G. 2018. The experience of probabilistic modeling and optimization of a centralized heat supply system which is an object for modernization. Proceedings of International Conference on Physics, Computing and Mathematical Modeling (PCMM), Shanghai, DEStech Publications, Inc., 93-97.
• [28] Kostogryzov, A., Nistratov, A., Nistratov, G., Atakishchev, O., Golovin, S. & Grigoriev, L. 2018. The probabilistic analysis of the possibilities to keep “organism integrity” by continuous monitoring. Proceedings of the International Conference on Mathematics, Modelling, Simulation and Algorithms (MMSA), Chengdu, China. Atlantis Press, Advances in Intelligent Systems Research, volume 159, 432-435.
• [29] Kostogryzov, A., Nistratov, A., Zubarev, I., Stepanov, P. & Grigoriev L. 2015. About accuracy of risks prediction and importance of increasing adequacy of used adequacy of used probabilistic models. Journal of Polish Safety and Reliability Association. Summer Safety and Reliability Seminars 6(2), 71-80.
• [30] Kostogryzov, A., Nistratov, G. & Nistratov, A. 2013. The innovative probability models and software technologies of risks prediction for systems operating in various fields. International Journal of Engineering and Innovative Technology (IJEIT) 3(3), 146-155.
• [31] Kostogryzov, A., Nistratov, G. & Nistratov, A. 2012. Some applicable methods to analyze and optimize system processes in quality management. Total quality management and Six Sigma, InTech, 127-196.
• [32] Kostogryzov, A., Panov, V., Stepanov, P., Grigoriev, L., Nistratov, A. & Nistratov, G. 2017. Optimization of sequence of performing heterogeneous repair work for transport systems by criteria of timeliness. Proceedings of the 4th International Conference on Transportation Information and Safety (ICTIS), Canada, Banff, 872-876.
• [33] Kostogryzov, A., Stepanov, P., Grigoriev, L., Atakishchev, O., Nistratov, A. & Nistratov, G. 2017. Improvement of existing risks control concept for complex systems by the automatic combination and generation of probabilistic models and forming the storehouse of risks predictions knowledge. Proceedings of the 2nd International Conference on Applied Mathematics, Simulation and Modelling (AMSM), Phuket, Thailand. DEStech Publications, Inc., 279-283.
• [34] Kostogryzov, A., Stepanov, P., Nistratov, A. & Atakishchev, O. 2017. About probabilistic risks analysis during longtime grain storage. Proceedings of the 2nd Internationale Conference on the Social Science and Teaching Research (ACSS–SSTR) 18 (Advances in Social and Behavioral Science. Singapore Management and Sports Science Institute), PTE.Ltd., 3-8.
• [35] Kostogryzov, A., Stepanov, P., Nistratov, A., Nistratov, G., Klimov, S. & Grigoriev, L. 2017. The method of rational dispatching a sequence of heterogeneous repair works. Energetica 63(4), 154-162.
• [36] Martin, J. 1972. System Analysis for Data Transmission. V. II, IBM System Research Institute. Prentice Hall, Inc., Englewood Cliffs, New Jersey.
• [37] Matweev, V. F. & Ushakov, V. G. 1984. Queuing systems. MSU, Moscow.
• [38] Silhavy, R., Silhavy, P. & Prokopova, Z. 2017. Cybernetics approaches in intelligent systems. Computational Methods in Systems and Software Vol. 1, Springer.
• [39] Zio, E. 2006. An Introduction to the Basics of Reliability and Risk Analysis, World Scientific Publishing Co.Pte.Ltd.